Data Visualisation

Postgraduate Diploma Data Visualisation.

What is Data Visualisation?
Data visualisation is a specialism concerned with producing visual representations (e.g. charts, graphs, maps, interactive dashboards, etc.) of datasets that effectively communicate the underlying patterns and key insights therein. The world is awash with data, and the rate at which data is being generated, stored and analysed is increasing exponentially along with advances in technology and its growing ubiquity in our daily lives. This programme aims to produce graduates equipped to work with this data to draw out valuable insights to inform meaningful actions toward successful outcomes. It is vital in any modern organisation to make data-driven decisions and communicate these effectively and ethically to stakeholders.

What will I do?
You will gain the knowledge, skills and competencies required by data visualisation designers and developers. These include sourcing and working with data; visual design principles; choosing appropriate visualisation modes; the grammar of graphics; technical/software skills to manipulate, explore, and create (interactive) visualisations; research and evaluation techniques to assess the requirements of a visualisation project and appraise the outcome. Throughout the programme, you will apply these skills and knowledge at each stage of the data visualisation design process from problem definition through to iterative design, prototyping and testing.

The learning environment of the programme is built around the practical application of theory and skills introduced in lectures, demonstrated in computer laboratories and applied in studio project work. This is supported by regular formative assessment and feedback enabling learners to engage in iterative development.

This programme is designed for candidates who are:
• already working in data science, information design, or graphic design, and; who are looking to broaden and deepen their knowledge;

• or those who are looking to retrain and up-skill in order to break into the field of data visualisation.

Subjects taught

What Modules will I study?
Term 1:
Data Visualisation; Contemporary Issues in Data; Designing With Data.

Term 2:
Advanced Data Visualisation; Applied Data Analytics; Professional Practice.

Entry requirements

Minimum Entry Requirements
An undergraduate degree at Level 8. Candidates who do not meet this requirement may apply under the IADT RPL policy.

Students intending to take this course will need to be proficient users of common word processing software, and of basic internet tools, have a basic grasp of spreadsheet and database software, and be willing, and keen to develop advanced user skills in those areas, and explore new technologies.

Application dates

Application Deadline: 03/09/2021.


Indicative Weekly Student Timetable:

Term 1: Oct 2021-Jan 2022.

Mon 10am-1pm [On campus]
Data Visualisation
Mon 2pm-5pm [On campus]
Data Visualisation

Tues 10am-1pm [Online]
Designing With Data
Tues 2pm-4pm [Online]
Data Visualisation

Weds 11am-1pm [Online] Contemporary Issues in Data

Term 2: Jan 2022-May 2022.

Mon 10am-1pm [On campus]
Applied Data Analytics
Mon 2pm-5pm [On campus]
Applied Data Analytics

Tuesday 11am-1pm [Online]
Advanced Data Visualisation
Tues 2pm-4pm [Online]
Advanced Data Visualisation

+ Weekly advisor meeting Professional Practice.

Post Course Info

Future Careers
Successful graduates will be equipped with the knowledge, skills and competencies to work across a wide range of data visualisation projects and roles in any industry that is reliant on working with and understanding data, such as: technology (big data / data science); news and media, finance, biotech, government; etc. Graduates will gain real-world experience through the Professional Practice module that will prepare them for their future careers.

Upon completion of the programme graduates will also be positioned to pursue further study pathways, e.g. at Masters or PhD level.

More details
  • Qualification letters


  • Qualifications

    Postgraduate Diploma (Level 9 NFQ)

  • Attendance type

    Part time,Daytime

  • Apply to

    Course provider